Automatic Fingerprint Identification Systems (herein after referred as “AFIS”) is an essential component of effective personal identification, as fingerprint features are easy to use, difficult to share and cannot be misplaced or handed over to others. The fingerprints intrinsically represent bodily identity of an individual, therefore the fingerprints are considered more reliable than traditional token based (ID card) systems or passwords. Every individual human being has unique features on the fingerprint and they remain constant for the entire lifetime of the individual. This is a reason, why use of the AFIS is growing day by day.
Performance of the AFIS at present degrades mainly because of following three problems:                Interoperability issue,        Non-linear elastic distortion, and        Partial fingerprint impressions.        
These issues limit large scale deployment of the AFIS in a distributive manner.
Before solving interoperability issue, it is important to identify what are the sources of it. There are differences in technology and working principle of existing fingerprint sensors. The basic difference is in the interaction means used by the existing fingerprint sensors. There are touch, swipe and touch free fingerprint identification devices. The sensors used in these devices are optical sensors, capacitive sensors, thermal sensors and the like. Characteristics of each of the sensor, such as physical design, resolution and capture area determines type and quality of the fingerprint image.
Interoperability Issue in AFIS is as Follows:
Biometric sensor interoperability refers to the ability of a system to compensate for the variability introduced in the raw biometric data image of an individual due to use of different sensors (here biometric data refers to digital copy of fingerprint images). It is observed that performance of most of the AFIS drops when two different sensors/devices/scanners are used for enrollment and verification. Most fingerprint matchers there-fine have restricted ability to compare fingerprints originating from two different sensors/devices, which results in poor inter-sensor detection.
Issues Relating to Non-Linear Elastic Distortions of Fingerprint Image:
Fingerprint image generation is a process of mapping 3D ridge structure on the plane surface of the sensor. Due to variations of skin elasticity and applied pressure some non-linear distortions are introduced in the fingerprint image. These non-linear distortions are difficult to model priori due to inconsistency of elasticity and pressure. Also, these non-linear distortions are not consistent in different types of sensors. The non-linear distortions are responsible for unnecessary false rejections. In order to incorporate these false-rejection of the images, the system and the method has to be operated with high false accept rate which is very dangerous and not acceptable for security application. It clearly shows huge performance drop when cross-compared between two databases.
Issues Related to Partial Fingerprint Images:
Partial fingerprint matching is still a challenging problem. Now a day, fingerprint authentication on handheld commercial devices like cell phones, laptops etc, are gaining lot, of popularity. Such devices are equipped with fingerprint sensors with very small capture area which results in acquisition of different parts of the same finger in multiple acquisitions. Most of the minutiae based fingerprint matching algorithms fail to incorporate such situation.